Triple
T1470410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finnair |
E27121
|
entity |
| Predicate | hasLoyaltyCurrency |
P13356
|
FINISHED |
| Object | Finnair Plus points |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Finnair Plus points | Statement: [Finnair, hasLoyaltyCurrency, Finnair Plus points]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLoyaltyCurrency Context triple: [Finnair, hasLoyaltyCurrency, Finnair Plus points]
-
A.
supportsLoyaltyCards
Indicates that an entity provides functionality to accept, manage, or work with loyalty cards for rewards or benefits.
-
B.
loyaltyProgramEarnings
Indicates the amount or details of rewards or benefits a participant accrues within a loyalty or rewards program.
-
C.
hasCredit
Indicates that an entity possesses or is assigned a credit, such as financial credit, academic credit, or acknowledgment for a contribution.
-
D.
hasMembershipProgram
chosen
Indicates that an entity offers or participates in a structured membership program, typically providing special access, benefits, or services to enrolled members.
-
E.
hasMonetaryComponent
Indicates that something includes, involves, or is associated with a monetary or financial element.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a496d25d6881909dbd84f86d763992 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c5d9dd4c8190ba840a9255cd1293 |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48350d88190a81bd149103f93e3 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:01 p.m.